Add getVarPseudocostScore and getVarPseudocost

CHANGELOG.md

@@ -13,6 +13,7 @@
 - Generalized getLhs() and getRhs() to additionally support any linear type constraint
 - Added recipe for getting local constraints
 - Added enableDebugSol() and disableDebugSol() for controlling the debug solution mechanism if DEBUGSOL=true
+- Added getVarPseudocostScore() and getVarPseudocost()
 ### Fixed
 - Raised an error when an expression is used when a variable is required
 - Fixed some compile warnings

src/pyscipopt/scip.pxd

@@ -810,6 +810,7 @@ cdef extern from "scip/scip.h":
     void SCIPvarMarkDeletable(SCIP_VAR* var)
     SCIP_Bool SCIPvarIsDeletable(SCIP_VAR* var)
     SCIP_Real SCIPgetVarPseudocost(SCIP* scip, SCIP_VAR* var, SCIP_BRANCHDIR dir)
+    SCIP_Real SCIPgetVarPseudocostScore(SCIP* scip, SCIP_VAR* var, SCIP_Real solval)
     SCIP_Real SCIPvarGetCutoffSum(SCIP_VAR* var, SCIP_BRANCHDIR dir)
     SCIP_Longint SCIPvarGetNBranchings(SCIP_VAR* var, SCIP_BRANCHDIR dir)
     SCIP_Bool SCIPvarMayRoundUp(SCIP_VAR* var)

src/pyscipopt/scip.pxi

@@ -308,7 +308,7 @@
     if rc == SCIP_OKAY:
         pass
     elif rc == SCIP_ERROR:
         raise Exception('SCIP: unspecified error!')
     elif rc == SCIP_NOMEMORY:
         raise MemoryError('SCIP: insufficient memory error!')
     elif rc == SCIP_READERROR:
@@ -4437,6 +4437,40 @@
             var_dict[var.name] = self.getVal(var)
         return var_dict
 
+    def getVarPseudocostScore(self, Variable var, solVal):
+        """
+        gets the variable's pseudo cost score value for the given LP solution value
+
+        Parameters
+        ----------
+        variable : Variable
+            problem variable
+        solVal : float
+            difference of variable's new LP value - old LP value
+
+        Returns
+        -------
+        float
+        """
+        return SCIPgetVarPseudocostScore(self._scip, var.scip_var, solVal)
+
+    def getVarPseudocost(self, Variable var, branchdir):
+        """
+        gets the variable's pseudo cost value for the given direction
+
+        Parameters
+        ----------
+        variable : Variable
+            problem variable
+        branchdir : PY_SCIP_BRANCHDIR
+            branching direction (downwards, or upwards)
+
+        Returns
+        -------
+        float
+        """
+        return SCIPgetVarPseudocost(self._scip, var.scip_var, branchdir)
+
     def updateNodeLowerbound(self, Node node, lb):
         """
         If given value is larger than the node's lower bound (in transformed problem),

tests/test_model.py

@@ -2,7 +2,7 @@
 import os
 import itertools
 
-from pyscipopt import Model, SCIP_STAGE, SCIP_PARAMSETTING, quicksum
+from pyscipopt import Model, SCIP_STAGE, SCIP_PARAMSETTING, SCIP_BRANCHDIR, quicksum
 from helpers.utils import random_mip_1
 
 def test_model():
@@ -528,3 +528,41 @@ def test_comparisons():
     assert not model.isNegative(0.)
 
     assert model.isHugeValue(inf)
+
+def test_getVarPseudocostScore():
+    m = Model()
+
+    m.addVar("x", vtype='B', obj=1.0)
+    m.addVar("y", vtype='B', obj=2.0)
+
+    m.setPresolve(SCIP_PARAMSETTING.OFF)
+    m.presolve()
+
+    var = m.getVars(transformed=True)[0]
+
+    p = m.getVarPseudocostScore(var, 1)
+    assert m.isEQ(p, 1)
+
+    p = m.getVarPseudocostScore(var, 0.5)
+    assert m.isEQ(p, 0.25)
+
+
+def test_getVarPseudocost():
+    m = Model()
+
+    m.addVar("x", vtype='B', obj=1.0)
+    m.addVar("y", vtype='B', obj=2.0)
+
+    m.setPresolve(SCIP_PARAMSETTING.OFF)
+    m.presolve()
+
+    var = m.getVars(transformed=True)[0]
+
+    p = m.getVarPseudocost(var, SCIP_BRANCHDIR.UPWARDS)
+    assert m.isEQ(p, 1)
+
+    m.updateVarPseudocost(var, 1, 12, 1)
+    p = m.getVarPseudocost(var, SCIP_BRANCHDIR.UPWARDS)
+
+    # Not exactly 12 because thw new value is a weighted sum of the all the updates
+    assert m.isEQ(p, 12.0001)